Dominant Strategy : Sell
Time series to forecast n: 04 Jun 2023 for (n+1 year)
Methodology : Modular Neural Network (Financial Sentiment Analysis)
Abstract
CITY OF LONDON INVESTMENT GROUP PLC prediction model is evaluated with Modular Neural Network (Financial Sentiment Analysis) and Linear Regression1,2,3,4 and it is concluded that the LON:CLIG stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: SellKey Points
- What statistical methods are used to analyze data?
- How accurate is machine learning in stock market?
- Operational Risk
LON:CLIG Target Price Prediction Modeling Methodology
We consider CITY OF LONDON INVESTMENT GROUP PLC Decision Process with Modular Neural Network (Financial Sentiment Analysis) where A is the set of discrete actions of LON:CLIG stock holders, F is the set of discrete states, P : S × F × S → R is the transition probability distribution, R : S × F → R is the reaction function, and γ ∈ [0, 1] is a move factor for expectation.1,2,3,4
F(Linear Regression)5,6,7= X R(Modular Neural Network (Financial Sentiment Analysis)) X S(n):→ (n+1 year)
n:Time series to forecast
p:Price signals of LON:CLIG stock
j:Nash equilibria (Neural Network)
k:Dominated move
a:Best response for target price
For further technical information as per how our model work we invite you to visit the article below:
How do AC Investment Research machine learning (predictive) algorithms actually work?
LON:CLIG Stock Forecast (Buy or Sell) for (n+1 year)
Sample Set: Neural NetworkStock/Index: LON:CLIG CITY OF LONDON INVESTMENT GROUP PLC
Time series to forecast n: 04 Jun 2023 for (n+1 year)
According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Sell
X axis: *Likelihood% (The higher the percentage value, the more likely the event will occur.)
Y axis: *Potential Impact% (The higher the percentage value, the more likely the price will deviate.)
Z axis (Grey to Black): *Technical Analysis%
IFRS Reconciliation Adjustments for CITY OF LONDON INVESTMENT GROUP PLC
- If there are changes in circumstances that affect hedge effectiveness, an entity may have to change the method for assessing whether a hedging relationship meets the hedge effectiveness requirements in order to ensure that the relevant characteristics of the hedging relationship, including the sources of hedge ineffectiveness, are still captured.
- That the transferee is unlikely to sell the transferred asset does not, of itself, mean that the transferor has retained control of the transferred asset. However, if a put option or guarantee constrains the transferee from selling the transferred asset, then the transferor has retained control of the transferred asset. For example, if a put option or guarantee is sufficiently valuable it constrains the transferee from selling the transferred asset because the transferee would, in practice, not sell the transferred asset to a third party without attaching a similar option or other restrictive conditions. Instead, the transferee would hold the transferred asset so as to obtain payments under the guarantee or put option. Under these circumstances the transferor has retained control of the transferred asset.
- To the extent that a transfer of a financial asset does not qualify for derecognition, the transferor's contractual rights or obligations related to the transfer are not accounted for separately as derivatives if recognising both the derivative and either the transferred asset or the liability arising from the transfer would result in recognising the same rights or obligations twice. For example, a call option retained by the transferor may prevent a transfer of financial assets from being accounted for as a sale. In that case, the call option is not separately recognised as a derivative asset.
- A hedge of a firm commitment (for example, a hedge of the change in fuel price relating to an unrecognised contractual commitment by an electric utility to purchase fuel at a fixed price) is a hedge of an exposure to a change in fair value. Accordingly, such a hedge is a fair value hedge. However, in accordance with paragraph 6.5.4, a hedge of the foreign currency risk of a firm commitment could alternatively be accounted for as a cash flow hedge.
*International Financial Reporting Standards (IFRS) adjustment process involves reviewing the company's financial statements and identifying any differences between the company's current accounting practices and the requirements of the IFRS. If there are any such differences, neural network makes adjustments to financial statements to bring them into compliance with the IFRS.
Conclusions
CITY OF LONDON INVESTMENT GROUP PLC is assigned short-term Ba1 & long-term Ba1 estimated rating. CITY OF LONDON INVESTMENT GROUP PLC prediction model is evaluated with Modular Neural Network (Financial Sentiment Analysis) and Linear Regression1,2,3,4 and it is concluded that the LON:CLIG stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Sell
LON:CLIG CITY OF LONDON INVESTMENT GROUP PLC Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | Ba1 | Ba1 |
Income Statement | B2 | Baa2 |
Balance Sheet | Baa2 | Caa2 |
Leverage Ratios | B2 | B3 |
Cash Flow | B2 | Caa2 |
Rates of Return and Profitability | Baa2 | C |
*Financial analysis is the process of evaluating a company's financial performance and position by neural network. It involves reviewing the company's financial statements, including the balance sheet, income statement, and cash flow statement, as well as other financial reports and documents.
How does neural network examine financial reports and understand financial state of the company?
Prediction Confidence Score

References
- Breiman L. 2001b. Statistical modeling: the two cultures (with comments and a rejoinder by the author). Stat. Sci. 16:199–231
- Robins J, Rotnitzky A. 1995. Semiparametric efficiency in multivariate regression models with missing data. J. Am. Stat. Assoc. 90:122–29
- Bell RM, Koren Y. 2007. Lessons from the Netflix prize challenge. ACM SIGKDD Explor. Newsl. 9:75–79
- Semenova V, Goldman M, Chernozhukov V, Taddy M. 2018. Orthogonal ML for demand estimation: high dimensional causal inference in dynamic panels. arXiv:1712.09988 [stat.ML]
- Athey S. 2017. Beyond prediction: using big data for policy problems. Science 355:483–85
- A. Y. Ng, D. Harada, and S. J. Russell. Policy invariance under reward transformations: Theory and application to reward shaping. In Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27 - 30, 1999, pages 278–287, 1999.
- R. Williams. Simple statistical gradient-following algorithms for connectionist reinforcement learning. Ma- chine learning, 8(3-4):229–256, 1992
Frequently Asked Questions
Q: What is the prediction methodology for LON:CLIG stock?A: LON:CLIG stock prediction methodology: We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) and Linear Regression
Q: Is LON:CLIG stock a buy or sell?
A: The dominant strategy among neural network is to Sell LON:CLIG Stock.
Q: Is CITY OF LONDON INVESTMENT GROUP PLC stock a good investment?
A: The consensus rating for CITY OF LONDON INVESTMENT GROUP PLC is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of LON:CLIG stock?
A: The consensus rating for LON:CLIG is Sell.
Q: What is the prediction period for LON:CLIG stock?
A: The prediction period for LON:CLIG is (n+1 year)